The poor correlation between fracture prevalence and bone mineral density has spurred the search for other parameters affecting the bone's mechanical competence. Although it has generally been assumed that the bone's intrinsic material properties remain unaltered in osteoporosis, there is strong evidence that this may not be the case. Specifically, the question has arisen whether parameters over and beyond material density, often summarized under the term "bone quality", may affect the bone's resistance to failure. Among the contributors conjectured to confer strength to bone, the structure of the trabecular network has received the greatest attention. Most prior work is based on histomorphometry or imaging of biopsy specimens. However, bone biopsy, because of its invasive nature, is usually not clinically indicated. In this project it is proposed to further develop and clinically evaluate the virtual bone biopsy, conceived in the investigators' laboratory, for assessing trabecular network integrity. The method is based on in vivo magnetic resonance microscopy (IMRI) and involves acquisition of 3D images of a representative volume comprising trabecular bone and marrow at a peripheral surrogate site (distal radius, distal tibia, calcaneus) and at a resolution sufficient to resolve the structural elements. The images are then subjected to a cascade of image restoration and processing steps yielding complete quantitative characterization of the trabecular bone network's three-dimensional topological make-up and scale. Prior work in the investigators' laboratory demonstrates that mu-MRI-derived architectural parameters are strong predictors of the bone's stiffness and provide a detailed picture of the etiology of postmenopausal osteoporotic bone loss, which is a conversion of trabecular plates to rods and disruption of rods. The overall hypothesis of this proposal is that the mu-MRI-based in vivo virtual bone biopsy provides detailed quantitative insight into the architectural implications of bone loss and that it discriminates patients with vertebral fractures from their gender and bone mineral density matched peers.